Description
Mathematical Statistics for Applied Econometrics
Author: Moss Charles B
Language: EnglishSubjects for Mathematical Statistics for Applied Econometrics:
Keywords
Distribution Functions; Cumulative Distribution Function; basics of statistical inference; Random Variable; nonlinear econometric techniques; Continuous Random Variable; econometric formulations; Posterior Distribution; statistical tools and econometric applications; Quantile Regression; Matrix Analysis; Linear Unbiased Estimator; Introductory Econometrics Text; Absolute Deviation Estimator; mathematical statistics for analyzing economic decisions under risk and uncertainty; Discrete Random Variable; Degree Stochastic Dominance; Α10 Α20α11 Α21 Α21 Α22; Bivariate Uniform Distribution; Inverse Hyperbolic Sine Transformation; Y11 Y12 Y21 Y22 Y31; Estimated Intervention Parameter; Bivariate Random Variable; Borel Set; Traditional Frequentist Approach; Real Number Line; Xb Xa; Yb Ya; Dummy Variable; General Maximum Likelihood Estimator; Maximum Likelihood Estimator; Medicare Drug Plans
Support: Print on demand
Description
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An Introductory Econometrics Text
Mathematical Statistics for Applied Econometrics covers the basics of statistical inference in support of a subsequent course on classical econometrics. The book shows students how mathematical statistics concepts form the basis of econometric formulations. It also helps them think about statistics as more than a toolbox of techniques.
Uses Computer Systems to Simplify Computation
The text explores the unifying themes involved in quantifying sample information to make inferences. After developing the necessary probability theory, it presents the concepts of estimation, such as convergence, point estimators, confidence intervals, and hypothesis tests. The text then shifts from a general development of mathematical statistics to focus on applications particularly popular in economics. It delves into matrix analysis, linear models, and nonlinear econometric techniques.
Students Understand the Reasons for the Results
Avoiding a cookbook approach to econometrics, this textbook develops students? theoretical understanding of statistical tools and econometric applications. It provides them with the foundation for further econometric studies.
DEFINING RANDOM VARIABLES: Introduction to Statistics, Probability and Econometrics. Random Variables and Probability Distributions. Moments and Moment Generating Functions. Binomial and Normal Random Variables. ESTIMATION: Large Sample Theory. Point Estimation. Interval Estimation. Testing Hypothesis. ECONOMETRIC APPLICATIONS: Elements of Matrix Analysis. Regression Applications in Econometrics. Notes. Bibliography. Index.
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